Portable navigation devices (PNDs) that include GNSS (Global Navigation Satellite Systems) signal reception and processing functionality are well known and are widely employed as in-car or other vehicle navigation systems. Such devices include a GNSS antenna, such as a GPS antenna, by means of which satellite-broadcast signals, including location data, can be received and subsequently processed to determine a current location of the device. The device may also include electronic gyroscopes and accelerometers which produce signals that can be processed to determine the current angular and linear acceleration. The determined acceleration may then be used in conjunction with location information derived from the GPS signal to determine the velocity and relative displacement of the device and thus vehicle in which it is typically mounted. Such sensors are most commonly provided in in-vehicle navigation systems, but may also be provided in the PND itself.
In recent years, GPS has also been used in systems to warn drivers of speed traps, enforcement cameras and road hazards, such as school zones, accident black spots, etc. In such systems, a device having a GPS antenna and access to a database containing the location of speed traps, accident black spots, etc is typically provided in a vehicle. The device is configured to provide warnings to a driver when the vehicle, using the location information derived from the GPS signal, is in the vicinity of one of the locations stored in the database. One such system is described, for example, in WO 01/55744 A2.
As will be appreciated by those skilled in the art, one of the important aspects of such systems is the accuracy and freshness of the information in the database. For example, it is undesirable to provide a warning to a user of a speed camera that is no longer present on the stretch of road, or to incorrectly indicate the speed limit on a stretch road associated with a speed camera in the database. In an effort to improve accuracy and freshness of such data, it is known to collect and utilise reports from drivers and other users indicating the presence or absence of speed cameras, and to provide this updated information to other members of the community in a real-time manner.
An example of one such system is the Trapster® application for mobile devices. In this application, all users of the app are asked to report or validate the status of speed traps, enforcement cameras and the like. As result of these reports, a digital map can be shown to a user with various icons and colours representing different trap types, and in some cases their associated confidence levels. For example: a green trap icon is displayed to indicate the presence of an unverified trap; a yellow trap icon is displayed to indicate that a trap has been verified by another user; a red trap icon is displayed to indicate that a trap has been verified by multiple users, and thus has the highest confidence level associated with it. The application also allows users to report relatively short-lived hazards, such as: police traps, e.g. an active sighting of a police speed trap, or a police vehicle currently observing traffic; construction zones, e.g. road works; brush fires; road closures; children at play; icy roads; etc. These hazards are shown to other users, again by means of an icon on the digital map, but will automatically expire after a certain period of time following the last positive report from a user confirming its presence. The particular period of time that elapses before a hazard is no longer shown to a user varies based on the type of hazard. For example, a police trap expires after one hour, road closures after six hours and a construction zone after five days.
Despite the improvements in speed trap and enforcement camera warning systems through the use of so-called active community feedback, e.g. as described above in relation to the Trapster® application, there remains scope for further improvement, and in particular with respect to the accuracy of the data in the associated database. More generally, there is a need to provide improved methods for obtaining and using data regarding the duration time information for dynamic POI. Current techniques tend to assign a fixed duration to a given dynamic POI dependent upon factors such as country, functional road class associated with the POI, POI type etc. However, it has been found that this may not adequately reflect durations of POI in practice.